1. Field of the Invention
The present invention relates generally to the field of equalizers for use in digital communications and, more particularly, to an improved decision feedback equalizer for use in time division multiple access communications.
2. Discussion of the Prior Art
An ideal communication link is characterized by a transfer function having a flat amplitude response and linear phase response as a function of frequency. In practice, however, deviations from the ideal occur and cause distortion and interference with a signal transmitted via the link. The causes of such deviations include communication devices (e.g., filters) and communication channels whose characteristics vary over time or space or both.
Consider the example of a cellular telephone system where a transceiver is used to place or receive a call from an arbitrary location within a service area or while moving through the area. The radio communication channel between the transceiver and the base station that processes the call is subject to the multipath phenomenon caused by buildings, terrain features and the like. In general, the multipath phenomenon causes the transfer function of the radio communication channel to become frequency dependent. In addition, if the transceiver is moving, the amplitude of the received signal may vary with time over a wide dynamic range, a phenomenon known as "fading."
To compensate for deviations in the transfer function, a device known as an equalizer may be used. The equalizer receives a transmitted signal and compensates, as ideally as possible, for distortion or interference caused by variations in the transfer function of the communication link. Stated another way, the function of an equalizer is to estimate what distortion or interference is present in a received signal and modify that signal to obtain a "true" representation of the signal that was actually transmitted.
Various types of equalizers are known in the prior art. One type, known as adaptive equalizers, are used in applications where the transfer function of a communication link varies with time, as in the example described above. An adaptive equalizer operates in accordance with a specified error-minimizing algorithm to dynamically modify a received signal to minimize the error between the received signal and a reference or assumed "true" signal. Two well known algorithms are recursive least square (RLS) and least mean square (LMS).
In order to initialize themselves to properly modify a received signal, adaptive equalizers follow a "training" procedure. Training is accomplished by transmitting to the equalizer a training signal (e.g., a particular sequence of symbols) which is known by the equalizer in advance. As the training signal is received, the equalizer is required to converge and adjust its signal-modification circuitry such that a minimum error is obtained in accordance with the operative error-minimizing algorithm. Through the training process, the equalizer effectively configures itself to substantially compensate for distortion or interference introduced by a given communication link under prevailing environmental conditions.
However, under dynamic conditions (e.g., a communication channel having a time-varying transfer function), the equalizer may lose track of the received signal and begin to make improper modification of that signal resulting in erroneous operation. In this error condition, the equalizer is sometimes said to be "lost." A conventional technique for recovering from a lost condition is to simply retrain the equalizer. That is, a training (retraining) signal is transmitted to the equalizer, which is again forced to converge and readjust its signal-modification circuitry.
There are several problems with conventional adaptive equalizers which render their performance inadequate for many applications. First, in time division multiple access (TDMA) communications, information is transmitted in pre-assigned time slots or frames by multiple transmitters over a shared communication channel. If a particular equalizer becomes lost in the middle of a frame, the equalizer may not be able to retrain until the end of that frame, which generally results in the loss of any subsequent data in that frame and a requirement of retransmission in a later frame. Obviously, as the number of required retransmissions increases, there is a corresponding decrease in the number of frames available for transmission of other data.
Second, since a conventional equalizer operates with a fixed convergence rate, that rate must represent a trade-off between the need to converge (complete training) within a given maximum time and the desire to train the equalizer as accurately as possible by allowing a longer training period. Also, during channel tracking, the equalizer may be incapable of adapting fast enough to properly track changes in the received signal if the transfer function of the communication channel changes too rapidly or over a larger than expected dynamic range.